https://bitbucket.org/edge-team-leat/microai_public
공식 코드Quantization and Deployment of Deep Neural Networks on Microcontrollers
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Quantization and Deployment of Deep Neural Networks on Microcontrollers
Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures
Frequency Perception Network for Camouflaged Object Detection
Global-and-Local Collaborative Learning for Co-Salient Object Detection
CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection
W2N:Switching From Weak Supervision to Noisy Supervision for Object Detection
Instant Response Few-shot Object Detection with Meta Strategy and Explicit Localization Inference
UEMM-Air: A Synthetic Multi-modal Dataset for Unmanned Aerial Vehicle Object Detection
Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches
Believing is Seeing: Unobserved Object Detection using Generative Models
WalnutData: A UAV Remote Sensing Dataset of Green Walnuts and Model Evaluation
Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner
From Open Vocabulary to Open World: Teaching Vision Language Models to Detect Novel Objects
UnrealROX+: An Improved Tool for Acquiring Synthetic Data from Virtual 3D Environments
STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes
Theoretically Achieving Continuous Representation of Oriented Bounding Boxes
Event-Based Fusion for Motion Deblurring with Cross-modal Attention
TexLiDAR: Automated Text Understanding for Panoramic LiDAR Data
Stillleben: Realistic Scene Synthesis for Deep Learning in Robotics
FLAME Diffuser: Wildfire Image Synthesis using Mask Guided Diffusion
MISFIT-V: Misaligned Image Synthesis and Fusion using Information from Thermal and Visual
Utilizing Multi-step Loss for Single Image Reflection Removal
NiNformer: A Network in Network Transformer with Token Mixing Generated Gating Function
RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNets
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists
Control Distance IoU and Control Distance IoU Loss Function for Better Bounding Box Regression
Boundary-Aware Segmentation Network for Mobile and Web Applications
BirdNet+: End-to-End 3D Object Detection in LiDAR Bird's Eye View
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.