{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/transfer-learning/papers/44","list_of":"/task/transfer-learning","task":"Transfer Learning","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":44,"pages_in_order":104,"rows_per_page":100,"rows":[4301,4400],"of":10307,"counts":{"archive_papers_tagged":10307,"with_a_code_link":3502,"where_syntology_ran_a_sample":692,"not_listed_spam_title":0,"listed":10307,"listed_where_code_ran":692,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":563,"every_run_a_failure_of_syntologys_instrument":129,"listed_with_a_run_with_no_instrument_failure":563,"listed_every_run_a_failure_of_syntologys_instrument":129,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/transfer-learning","prev":"/task/transfer-learning/papers/43","next":"/task/transfer-learning/papers/45","papers":[{"url":null,"slug":"cross-modal-few-shot-learning-a-generative","title":"Cross-Modal Few-Shot Learning: a Generative Transfer Learning Framework","date":"2024-10-14","arxiv_id":"2410.10663","repositories_listed":0,"syntology":null},{"url":null,"slug":"eegpt-unleashing-the-potential-of-eeg","title":"EEGPT: Unleashing the Potential of EEG Generalist Foundation Model by Autoregressive Pre-training","date":"2024-10-14","arxiv_id":"2410.19779","repositories_listed":0,"syntology":null},{"url":null,"slug":"model-based-differentially-private-knowledge","title":"Model-based Large Language Model Customization as Service","date":"2024-10-14","arxiv_id":"2410.10481","repositories_listed":0,"syntology":null},{"url":null,"slug":"spegcl-self-supervised-graph-spectrum","title":"SpeGCL: Self-supervised Graph Spectrum Contrastive Learning without Positive Samples","date":"2024-10-14","arxiv_id":"2410.10365","repositories_listed":0,"syntology":null},{"url":null,"slug":"tl-pca-transfer-learning-of-principal","title":"TL-PCA: Transfer Learning of Principal Component Analysis","date":"2024-10-14","arxiv_id":"2410.10805","repositories_listed":0,"syntology":null},{"url":null,"slug":"magnituder-layers-for-implicit-neural","title":"Magnituder Layers for Implicit Neural Representations in 3D","date":"2024-10-13","arxiv_id":"2410.09771","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-transfer-learning-model-framework-and","title":"Deep Transfer Learning: Model Framework and Error Analysis","date":"2024-10-12","arxiv_id":"2410.09383","repositories_listed":0,"syntology":null},{"url":null,"slug":"hey-ai-can-you-grade-my-essay-automatic-essay","title":"Hey AI Can You Grade My Essay?: Automatic Essay Grading","date":"2024-10-12","arxiv_id":"2410.09319","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-transfer-learning-empowered-temporal","title":"Meta-Transfer Learning Empowered Temporal Graph Networks for Cross-City Real Estate Appraisal","date":"2024-10-11","arxiv_id":"2410.08947","repositories_listed":0,"syntology":null},{"url":null,"slug":"unity-is-power-semi-asynchronous","title":"Unity is Power: Semi-Asynchronous Collaborative Training of Large-Scale Models with Structured Pruning in Resource-Limited Clients","date":"2024-10-11","arxiv_id":"2410.08457","repositories_listed":0,"syntology":null},{"url":null,"slug":"features-are-fate-a-theory-of-transfer","title":"Features are fate: a theory of transfer learning in high-dimensional regression","date":"2024-10-10","arxiv_id":"2410.08194","repositories_listed":0,"syntology":null},{"url":null,"slug":"federated-graph-learning-for-cross-domain","title":"Federated Graph Learning for Cross-Domain Recommendation","date":"2024-10-10","arxiv_id":"2410.08249","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-transferable-pruning","title":"Non-transferable Pruning","date":"2024-10-10","arxiv_id":"2410.08015","repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-and-security-enhancement-of-radio","title":"Robustness and Security Enhancement of Radio Frequency Fingerprint Identification in Time-Varying Channels","date":"2024-10-10","arxiv_id":"2410.07591","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-data-validation-methods-for","title":"Unsupervised Data Validation Methods for Efficient Model Training","date":"2024-10-10","arxiv_id":"2410.07880","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-is-left-after-distillation-how-knowledge","title":"What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias","date":"2024-10-10","arxiv_id":"2410.08407","repositories_listed":0,"syntology":null},{"url":null,"slug":"collusion-detection-with-graph-neural","title":"Collusion Detection with Graph Neural Networks","date":"2024-10-09","arxiv_id":"2410.07091","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-relationship-between-visual-anomaly","title":"On The Relationship between Visual Anomaly-free and Anomalous Representations","date":"2024-10-09","arxiv_id":"2410.06576","repositories_listed":0,"syntology":null},{"url":null,"slug":"recgnition-v1-0-arrhythmia-detection-using","title":"rECGnition_v1.0: Arrhythmia detection using cardiologist-inspired multi-modal architecture incorporating demographic attributes in ECG","date":"2024-10-09","arxiv_id":"2410.18985","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-a-class-of-cascade","title":"Transfer Learning for a Class of Cascade Dynamical Systems","date":"2024-10-09","arxiv_id":"2410.06828","repositories_listed":0,"syntology":null},{"url":null,"slug":"utilizing-transfer-learning-and-pre-trained","title":"Utilizing Transfer Learning and pre-trained Models for Effective Forest Fire Detection: A Case Study of Uttarakhand","date":"2024-10-09","arxiv_id":"2410.06743","repositories_listed":0,"syntology":null},{"url":null,"slug":"advancements-in-road-lane-mapping-comparative","title":"Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery","date":"2024-10-08","arxiv_id":"2410.05717","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-modalities-enhancing-cross-modality","title":"Bridging Modalities: Enhancing Cross-Modality Hate Speech Detection with Few-Shot In-Context Learning","date":"2024-10-08","arxiv_id":"2410.05600","repositories_listed":0,"syntology":null},{"url":null,"slug":"generating-synthetic-datasets-for-few-shot","title":"Generating Synthetic Datasets for Few-shot Prompt Tuning","date":"2024-10-08","arxiv_id":"2410.10865","repositories_listed":0,"syntology":null},{"url":null,"slug":"hyper-adversarial-tuning-for-boosting","title":"Hyper Adversarial Tuning for Boosting Adversarial Robustness of Pretrained Large Vision Models","date":"2024-10-08","arxiv_id":"2410.05951","repositories_listed":0,"syntology":null},{"url":null,"slug":"modalprompt-dual-modality-guided-prompt-for","title":"ModalPrompt:Dual-Modality Guided Prompt for Continual Learning of Large Multimodal Models","date":"2024-10-08","arxiv_id":"2410.05849","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-transfer-learning-for-active-level-set","title":"Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior","date":"2024-10-08","arxiv_id":"2410.05660","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-recurrent-neural-network-approach-to-the","title":"A Recurrent Neural Network Approach to the Answering Machine Detection Problem","date":"2024-10-07","arxiv_id":"2410.08235","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-based-visual-measurement","title":"Deep learning-based Visual Measurement Extraction within an Adaptive Digital Twin Framework from Limited Data Using Transfer Learning","date":"2024-10-07","arxiv_id":"2410.05403","repositories_listed":0,"syntology":null},{"url":"/paper/learning-interpretable-hierarchical-dynamical","slug":"learning-interpretable-hierarchical-dynamical","title":"Learning Interpretable Hierarchical Dynamical Systems Models from Time Series Data","date":"2024-10-07","arxiv_id":"2410.04814","repositories_listed":0,"syntology":{"n":4,"n_ran":3,"n_constructed":1,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-interpretable-hierarchical-dynamical#ran","syntology_url":"https://syntology.ai/paper/2410.04814","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.04814"}},"official":null}},{"url":null,"slug":"pre-ictal-seizure-prediction-using","title":"Pre-Ictal Seizure Prediction Using Personalized Deep Learning","date":"2024-10-07","arxiv_id":"2410.05491","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-transfer-learning-based-peer-review","title":"Deep Transfer Learning Based Peer Review Aggregation and Meta-review Generation for Scientific Articles","date":"2024-10-05","arxiv_id":"2410.04202","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpolation-free-deep-learning-for","title":"Interpolation-Free Deep Learning for Meteorological Downscaling on Unaligned Grids Across Multiple Domains with Application to Wind Power","date":"2024-10-04","arxiv_id":"2410.03945","repositories_listed":0,"syntology":null},{"url":null,"slug":"remaining-useful-life-prediction-a-study-on","title":"Remaining Useful Life Prediction: A Study on Multidimensional Industrial Signal Processing and Efficient Transfer Learning Based on Large Language Models","date":"2024-10-04","arxiv_id":"2410.03134","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-method-for-accurate-real-time-food","title":"A Novel Method for Accurate & Real-time Food Classification: The Synergistic Integration of EfficientNetB7, CBAM, Transfer Learning, and Data Augmentation","date":"2024-10-03","arxiv_id":"2410.02304","repositories_listed":0,"syntology":null},{"url":null,"slug":"ethio-fake-cutting-edge-approaches-to-combat","title":"Ethio-Fake: Cutting-Edge Approaches to Combat Fake News in Under-Resourced Languages Using Explainable AI","date":"2024-10-03","arxiv_id":"2410.02609","repositories_listed":0,"syntology":null},{"url":null,"slug":"qdgset-a-large-scale-grasping-dataset","title":"QDGset: A Large Scale Grasping Dataset Generated with Quality-Diversity","date":"2024-10-03","arxiv_id":"2410.02319","repositories_listed":0,"syntology":null},{"url":null,"slug":"reconstructing-human-mobility-pattern-a-semi","title":"Reconstructing Human Mobility Pattern: A Semi-Supervised Approach for Cross-Dataset Transfer Learning","date":"2024-10-03","arxiv_id":"2410.03788","repositories_listed":0,"syntology":null},{"url":null,"slug":"source-data-selection-for-brain-computer","title":"Source Data Selection for Brain-Computer Interfaces based on Simple Features","date":"2024-10-03","arxiv_id":"2410.02360","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-comparison-of-individual-cat-recognition","title":"The Comparison of Individual Cat Recognition Using Neural Networks","date":"2024-10-03","arxiv_id":"2410.02305","repositories_listed":0,"syntology":null},{"url":null,"slug":"universality-in-transfer-learning-for-linear","title":"Universality in Transfer Learning for Linear Models","date":"2024-10-03","arxiv_id":"2410.02164","repositories_listed":0,"syntology":null},{"url":null,"slug":"rs-fme-swint-a-novel-feature-map-enhancement","title":"RS-FME-SwinT: A Novel Feature Map Enhancement Framework Integrating Customized SwinT with Residual and Spatial CNN for Monkeypox Diagnosis","date":"2024-10-02","arxiv_id":"2410.01216","repositories_listed":0,"syntology":null},{"url":null,"slug":"advanced-arabic-alphabet-sign-language","title":"Advanced Arabic Alphabet Sign Language Recognition Using Transfer Learning and Transformer Models","date":"2024-10-01","arxiv_id":"2410.00681","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-intrinsically-knowledge-transferring","title":"An Intrinsically Knowledge-Transferring Developmental Spiking Neural Network for Tactile Classification","date":"2024-10-01","arxiv_id":"2410.00745","repositories_listed":0,"syntology":null},{"url":null,"slug":"emgttl-transformers-based-transfer-learning","title":"EMGTTL: Transformers-Based Transfer Learning for Classification of ADL using Raw Surface EMG Signals","date":"2024-10-01","arxiv_id":"2410.00586","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-multi-task-transfer-learning-for","title":"Scalable Multi-Task Transfer Learning for Molecular Property Prediction","date":"2024-10-01","arxiv_id":"2410.00432","repositories_listed":0,"syntology":null},{"url":null,"slug":"classroom-inspired-multi-mentor-distillation","title":"Classroom-Inspired Multi-Mentor Distillation with Adaptive Learning Strategies","date":"2024-09-30","arxiv_id":"2409.20237","repositories_listed":0,"syntology":null},{"url":null,"slug":"firelite-leveraging-transfer-learning-for","title":"FireLite: Leveraging Transfer Learning for Efficient Fire Detection in Resource-Constrained Environments","date":"2024-09-30","arxiv_id":"2409.20384","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-scale-convolutional-lstm-with-transfer","title":"Multi-Scale Convolutional LSTM with Transfer Learning for Anomaly Detection in Cellular Networks","date":"2024-09-30","arxiv_id":"2410.03732","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-topology-and-geometry-of-population","title":"On the topology and geometry of population-based SHM","date":"2024-09-30","arxiv_id":"2410.00923","repositories_listed":0,"syntology":null},{"url":null,"slug":"surgpetl-parameter-efficient-image-to","title":"SurgPETL: Parameter-Efficient Image-to-Surgical-Video Transfer Learning for Surgical Phase Recognition","date":"2024-09-30","arxiv_id":"2409.20083","repositories_listed":0,"syntology":null},{"url":null,"slug":"brain-tumor-classification-on-mri-in-light-of","title":"Brain Tumor Classification on MRI in Light of Molecular Markers","date":"2024-09-29","arxiv_id":"2409.19583","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-universality-of-neural-encodings-in","title":"On the universality of neural encodings in CNNs","date":"2024-09-28","arxiv_id":"2409.19460","repositories_listed":0,"syntology":null},{"url":null,"slug":"harmonizing-knowledge-transfer-in-neural","title":"Harmonizing knowledge Transfer in Neural Network with Unified Distillation","date":"2024-09-27","arxiv_id":"2409.18565","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-effective-is-pre-training-of-large-masked","title":"How Effective is Pre-training of Large Masked Autoencoders for Downstream Earth Observation Tasks?","date":"2024-09-27","arxiv_id":"2409.18536","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-rtl-reinforcement-based-meta-transfer","title":"Meta-RTL: Reinforcement-Based Meta-Transfer Learning for Low-Resource Commonsense Reasoning","date":"2024-09-27","arxiv_id":"2409.19075","repositories_listed":0,"syntology":null},{"url":null,"slug":"student-oriented-teacher-knowledge-refinement","title":"Student-Oriented Teacher Knowledge Refinement for Knowledge Distillation","date":"2024-09-27","arxiv_id":"2409.18785","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-segmentation-and-analysis-of","title":"Automated Segmentation and Analysis of Microscopy Images of Laser Powder Bed Fusion Melt Tracks","date":"2024-09-26","arxiv_id":"2409.18326","repositories_listed":0,"syntology":null},{"url":null,"slug":"jump-diffusion-informed-neural-networks-with","title":"Jump Diffusion-Informed Neural Networks with Transfer Learning for Accurate American Option Pricing under Data Scarcity","date":"2024-09-26","arxiv_id":"2409.18168","repositories_listed":0,"syntology":null},{"url":null,"slug":"t3-a-novel-zero-shot-transfer-learning","title":"T3: A Novel Zero-shot Transfer Learning Framework Iteratively Training on an Assistant Task for a Target Task","date":"2024-09-26","arxiv_id":"2409.17640","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-in-ell-1-regularized","title":"Transfer Learning in $\\ell_1$ Regularized Regression: Hyperparameter Selection Strategy based on Sharp Asymptotic Analysis","date":"2024-09-26","arxiv_id":"2409.17704","repositories_listed":0,"syntology":null},{"url":null,"slug":"speech-recognition-rescoring-with-large","title":"Speech Recognition Rescoring with Large Speech-Text Foundation Models","date":"2024-09-25","arxiv_id":"2409.16654","repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-advancements-of-low","title":"Machine Translation Advancements of Low-Resource Indian Languages by Transfer Learning","date":"2024-09-24","arxiv_id":"2409.15879","repositories_listed":0,"syntology":null},{"url":null,"slug":"personalized-federated-learning-via-backbone","title":"Personalized Federated Learning via Backbone Self-Distillation","date":"2024-09-24","arxiv_id":"2409.15636","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-financial-data","title":"Transfer learning for financial data predictions: a systematic review","date":"2024-09-24","arxiv_id":"2409.17183","repositories_listed":0,"syntology":null},{"url":null,"slug":"con-continual-object-navigation-via-data-free","title":"CON: Continual Object Navigation via Data-Free Inter-Agent Knowledge Transfer in Unseen and Unfamiliar Places","date":"2024-09-23","arxiv_id":"2409.14899","repositories_listed":0,"syntology":null},{"url":null,"slug":"micrometer-micromechanics-transformer-for","title":"Micrometer: Micromechanics Transformer for Predicting Mechanical Responses of Heterogeneous Materials","date":"2024-09-23","arxiv_id":"2410.05281","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-lazy-to-rich-exact-learning-dynamics-in","title":"From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks","date":"2024-09-22","arxiv_id":"2409.14623","repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-in-birdsong-classification","title":"Generalization in birdsong classification: impact of transfer learning methods and dataset characteristics","date":"2024-09-21","arxiv_id":"2409.15383","repositories_listed":0,"syntology":null},{"url":null,"slug":"multiple-exit-tuning-towards-inference","title":"Multiple-Exit Tuning: Towards Inference-Efficient Adaptation for Vision Transformer","date":"2024-09-21","arxiv_id":"2409.13999","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-and-machine-learning-advancing-4","title":"Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models","date":"2024-09-20","arxiv_id":"2409.13566","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-and-double-u-net-empowered","title":"Transfer Learning and Double U-Net Empowered Wave Propagation Model in Complex Indoor Environment","date":"2024-09-20","arxiv_id":"2409.13833","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-e-commerce-query","title":"Transfer Learning for E-commerce Query Product Type Prediction","date":"2024-09-20","arxiv_id":"2410.07121","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-with-clinical-concept","title":"Transfer Learning with Clinical Concept Embeddings from Large Language Models","date":"2024-09-20","arxiv_id":"2409.13893","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-transfer-hashing-for-adaptive-learning","title":"Deep Transfer Hashing for Adaptive Learning on Federated Streaming Data","date":"2024-09-19","arxiv_id":"2409.12575","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-bat-song-syllable-representations","title":"Exploring bat song syllable representations in self-supervised audio encoders","date":"2024-09-19","arxiv_id":"2409.12634","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigation-on-domain-adaptation-of","title":"Investigation on domain adaptation of additive manufacturing monitoring systems to enhance digital twin reusability","date":"2024-09-19","arxiv_id":"2409.12785","repositories_listed":0,"syntology":null},{"url":null,"slug":"rapid-aerodynamic-prediction-of-swept-wings","title":"Rapid aerodynamic prediction of swept wings via physics-embedded transfer learning","date":"2024-09-19","arxiv_id":"2409.12711","repositories_listed":0,"syntology":null},{"url":null,"slug":"recognition-of-harmful-phytoplankton-from","title":"Recognition of Harmful Phytoplankton from Microscopic Images using Deep Learning","date":"2024-09-19","arxiv_id":"2409.12900","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-domain-gap-for-flight-ready","title":"Bridging Domain Gap for Flight-Ready Spaceborne Vision","date":"2024-09-18","arxiv_id":"2409.11661","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-low-resolution-face-recognition-via","title":"Efficient Low-Resolution Face Recognition via Bridge Distillation","date":"2024-09-18","arxiv_id":"2409.11786","repositories_listed":0,"syntology":null},{"url":null,"slug":"location-based-probabilistic-load-forecasting","title":"Location based Probabilistic Load Forecasting of EV Charging Sites: Deep Transfer Learning with Multi-Quantile Temporal Convolutional Network","date":"2024-09-18","arxiv_id":"2409.11862","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-large-language-models-to-generate-3","title":"Using Large Language Models to Generate Clinical Trial Tables and Figures","date":"2024-09-18","arxiv_id":"2409.12046","repositories_listed":0,"syntology":null},{"url":null,"slug":"analysis-of-convolutional-neural-network-2","title":"Analysis of Convolutional Neural Network-based Image Classifications: A Multi-Featured Application for Rice Leaf Disease Prediction and Recommendations for Farmers","date":"2024-09-17","arxiv_id":"2410.01827","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-distillation-techniques-for","title":"Leveraging Distillation Techniques for Document Understanding: A Case Study with FLAN-T5","date":"2024-09-17","arxiv_id":"2409.11282","repositories_listed":0,"syntology":null},{"url":null,"slug":"unleashing-the-potential-of-mamba-boosting-a","title":"Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation","date":"2024-09-17","arxiv_id":"2409.11018","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparative-study-of-open-source-computer","title":"A Comparative Study of Open Source Computer Vision Models for Application on Small Data: The Case of CFRP Tape Laying","date":"2024-09-16","arxiv_id":"2409.10104","repositories_listed":0,"syntology":null},{"url":null,"slug":"rf-gml-reference-free-generative-machine","title":"RF-GML: Reference-Free Generative Machine Listener","date":"2024-09-16","arxiv_id":"2409.10210","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-impact-of-data-quantity-on-asr","title":"Exploring the Impact of Data Quantity on ASR in Extremely Low-resource Languages","date":"2024-09-13","arxiv_id":"2409.08872","repositories_listed":0,"syntology":null},{"url":null,"slug":"using-the-concept-hierarchy-for-household","title":"Using The Concept Hierarchy for Household Action Recognition","date":"2024-09-13","arxiv_id":"2409.08853","repositories_listed":0,"syntology":null},{"url":null,"slug":"dreambeast-distilling-3d-fantastical-animals","title":"DreamBeast: Distilling 3D Fantastical Animals with Part-Aware Knowledge Transfer","date":"2024-09-12","arxiv_id":"2409.08271","repositories_listed":0,"syntology":null},{"url":null,"slug":"dvs-blood-cancer-detection-using-novel-cnn","title":"DVS: Blood cancer detection using novel CNN-based ensemble approach","date":"2024-09-12","arxiv_id":"2410.05272","repositories_listed":0,"syntology":null},{"url":null,"slug":"learn-from-balance-rectifying-knowledge","title":"Learn from Balance: Rectifying Knowledge Transfer for Long-Tailed Scenarios","date":"2024-09-12","arxiv_id":"2409.07694","repositories_listed":0,"syntology":null},{"url":null,"slug":"music-auto-tagging-in-the-long-tail-a-few","title":"Music auto-tagging in the long tail: A few-shot approach","date":"2024-09-12","arxiv_id":"2409.07730","repositories_listed":0,"syntology":null},{"url":null,"slug":"reimagining-linear-probing-kolmogorov-arnold","title":"Reimagining Linear Probing: Kolmogorov-Arnold Networks in Transfer Learning","date":"2024-09-12","arxiv_id":"2409.07763","repositories_listed":0,"syntology":null},{"url":null,"slug":"spark-self-supervised-personalized-real-time","title":"SPARK: Self-supervised Personalized Real-time Monocular Face Capture","date":"2024-09-12","arxiv_id":"2409.07984","repositories_listed":0,"syntology":null},{"url":null,"slug":"theragen-therapy-for-every-generation","title":"TheraGen: Therapy for Every Generation","date":"2024-09-12","arxiv_id":"2409.13748","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-applied-to-computer-vision","title":"Transfer Learning Applied to Computer Vision Problems: Survey on Current Progress, Limitations, and Opportunities","date":"2024-09-12","arxiv_id":"2409.07736","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-techniques-for-hand-vein","title":"Deep Learning Techniques for Hand Vein Biometrics: A Comprehensive Review","date":"2024-09-11","arxiv_id":"2409.07128","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-neural-network-based-sign-language","title":"Deep Neural Network-Based Sign Language Recognition: A Comprehensive Approach Using Transfer Learning with Explainability","date":"2024-09-11","arxiv_id":"2409.07426","repositories_listed":0,"syntology":null}],"record_sha256":"640d972c783d9d68d60a1b8682cc01059d82996a18bc3c2151364f33df29d050","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}