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Image Classification
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Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Robust Training with Data Augmentation for Medical Imaging Classification
Efficient Transformations in Deep Learning Convolutional Neural Networks
J3DAI: A tiny DNN-Based Edge AI Accelerator for 3D-Stacked CMOS Image Sensor
Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference
FedWSIDD: Federated Whole Slide Image Classification via Dataset Distillation
One-Shot Neural Architecture Search with Network Similarity Directed Initialization for Pathological Image Classification
A Variational Information Theoretic Approach to Out-of-Distribution Detection
Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection
Compositional Attribute Imbalance in Vision Datasets
Train Once, Forget Precisely: Anchored Optimization for Efficient Post-Hoc Unlearning
DDS-NAS: Dynamic Data Selection within Neural Architecture Search via On-line Hard Example Mining applied to Image Classification
SeqPE: Transformer with Sequential Position Encoding
FindMeIfYouCan: Bringing Open Set metrics to $\textit{near} $, $ \textit{far} $ and $\textit{farther}$ Out-of-Distribution Object Detection
Finding Optimal Kernel Size and Dimension in Convolutional Neural Networks An Architecture Optimization Approach
Evaluating Cell Type Inference in Vision Language Models Under Varying Visual Context
Cross-architecture universal feature coding via distribution alignment
Intriguing Frequency Interpretation of Adversarial Robustness for CNNs and ViTs
CMI-Bench: A Comprehensive Benchmark for Evaluating Music Instruction Following
OscNet v1.5: Energy Efficient Hopfield Network on CMOS Oscillators for Image Classification
GPLQ: A General, Practical, and Lightning QAT Method for Vision Transformers
MRI-CORE: A Foundation Model for Magnetic Resonance Imaging
Graph Semi-Supervised Learning for Point Classification on Data Manifolds
Can We Infer Confidential Properties of Training Data from LLMs?
Boosting Adversarial Transferability for Hyperspectral Image Classification Using 3D Structure-invariant Transformation and Intermediate Feature Distance
Text to Image for Multi-Label Image Recognition with Joint Prompt-Adapter Learning
PiPViT: Patch-based Visual Interpretable Prototypes for Retinal Image Analysis
SNR and Resource Adaptive Deep JSCC for Distributed IoT Image Classification
DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding
Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection
Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers
Hyperspectral Image Classification via Transformer-based Spectral-Spatial Attention Decoupling and Adaptive Gating
An Adaptive Method Stabilizing Activations for Enhanced Generalization
Biologically Inspired Deep Learning Approaches for Fetal Ultrasound Image Classification
InceptionMamba: An Efficient Hybrid Network with Large Band Convolution and Bottleneck Mamba
Normalized Radon Cumulative Distribution Transforms for Invariance and Robustness in Optimal Transport Based Image Classification
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