arXiv AI

Beyond Backbone Backpropagation: A Decoupled Strategy for Efficient Transfer Learning

arXiv:2607. 13043v1 Announce Type: cross Abstract: Deep learning models achieve state-of-the-art image classification but face deployment challenges due to computational costs and energy demands.

Hugging Face Trending Papers

Jun 21

Multi-cancer detection using a computationally efficient CNN with transfer learning

This study introduces a computationally efficient convolutional neural network (CNN) architecture enhanced with transfer learning for multi-cancer detection using biomedical images. The proposed lightweight CNN model is designed to reduce computational complexity while maintaining high classification performance, making it suitable for deployment in resource-constrained environments.

fine-tuning benchmarks

arXiv AI

Aug 12

Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection

arXiv:2608. 09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis.

By Samar Garrab, Ghada Achour

llms benchmarks

arXiv AI

Jun 29

Automated brain tumor detection in MRI images using CNN and ResNet architectures

arXiv:2606. 27405v1 Announce Type: cross Abstract: Deep learning has shown significant potential in medical image analysis, particularly for disease detection using MRI scans.

By Annapurna V K, Asha N, K Paramesha, Shabana Sultana, Kirankumar Humse

fine-tuning

arXiv Machine Learning

Jun 10

Multimodal Brain Tumour Classification Using Feature Fusion

arXiv:2606. 11107v1 Announce Type: cross Abstract: Clinicians diagnose brain tumors by synthesizing patient symptoms, medical history, and quantitative imaging data from modalities such as MRI and CT scans into a unified clinical judgement.

By Wajih ul Islam, Muhammad Yaqoob, Javed Ali Khan, Volker Steuber

multimodal

arXiv Machine Learning

6d ago

A comparison of CNN architectures for Alzheimer's disease detection in single-view MRI scans

arXiv:2608. 11762v1 Announce Type: cross Abstract: Alzheimer's disease is a leading cause of death with no cure.

By Hiram Zuniga, Ulises Orozco-Rosas, Kenia Picos

fine-tuning benchmarks

arXiv AI

Jun 9

AMN: An Adaptive Multi-Scale Fusion Network with Boundary and Uncertainty Modeling for Nuclei Segmentation

arXiv:2606. 07633v1 Announce Type: cross Abstract: Accurate classification of nuclei subtypes in histopathology images is critical for downstream tasks including tumor grading, immune infiltrate quantification, and prognosis prediction.

By Spoorthi M, Suja Palaniswamy

llms computer-vision benchmarks

arXiv AI

Jun 30

A Deep Multiscale Neural Network for Accurate Neurological Disorder Detection from MRI Scans and Real-Time Web Deployment

arXiv:2606. 29106v1 Announce Type: cross Abstract: Neurological disorders involve diverse pathologies of the brain and nervous system, making early and accurate detection essential.

By Ali Fatahi, Hoda Zamani, Mohammad H. Nadimi-Shahraki

arXiv Machine Learning

Aug 3

MoPET: Parameter-Efficient Mixture-of-Experts for Unified Medical Image Classification

arXiv:2607. 29462v1 Announce Type: cross Abstract: Adapting deep learning models to profound clinical heterogeneity typically relies on parameter-efficient fine-tuning (PEFT) to avoid the severe overfitting associated with full end-to-end network updates.

By Sebastian Doerrich, Daniel W\"urtinger, Francesco Di Salvo, Shyam Nandan Rai, Christian Ledig

computer-vision fine-tuning benchmarks

arXiv AI

Jul 17

Pretraining Multiple Instance Learning Networks with Multi-Teacher Distillation from Pathology Slide Foundation Models

arXiv:2607. 14703v1 Announce Type: cross Abstract: Multiple instance learning (MIL) has become the main paradigm for whole-slide image (WSI) analysis in computational pathology.

By Mingxi Fu, Jiawen Li, Renao Yan, Jiali Hu, Qiehe Sun, Tian Guan, Yonghong He

llms computer-vision fine-tuning efficiency benchmarks

arXiv AI

Jun 10

Forward-Only Convolutional Neural Networks with Learnable Channel-Class Assignment

arXiv:2606. 09928v1 Announce Type: cross Abstract: The Forward-Forward (FF) algorithm offers a biologically inspired alternative to backpropagation by replacing gradient-based credit assignment with local, forward-only objectives.

By Mohammadnavid Ghader, Saeed Reza Kheradpisheh, Bahar Farahani, Mahmood Fazlali

benchmarks

Hugging Face Trending Papers

Jun 27

A Deep Multiscale Neural Network for Accurate Neurological Disorder Detection from MRI Scans and Real-Time Web Deployment

Neurological disorders involve diverse pathologies of the brain and nervous system, making early and accurate detection essential. While many deep CNNs have been developed for MRI-based classification of neurological disorders, most are optimized for binary tasks and often fail to capture the multi-class features needed to distinguish subtle anatomical differences across conditions.

arXiv AI

Jun 2

ResNet-34 with Lightweight Decoder for Accurate and Efficient Segmentation of Fetal Brain MRI

arXiv:2606. 01293v1 Announce Type: cross Abstract: Accurate segmentation of fetal brain tissues in Magnetic Resonance Imaging (MRI) is critical for early diagnosis of congenital abnormalities and improving prenatal care.

By Ashiqur Rahman, Muhammad E. H. Chowdhury, Md. Abu Sayed, Md. Sharjis Ibne Wadud, Abu Naser Md. Arafat, Mehedi Hasan Prince

computer-vision

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