https://github.com/islab-sophia/2s-odis
공식 코드2S-ODIS: Two-Stage Omni-Directional Image Synthesis by Geometric Distortion Correction
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A Brain-Computer Interface (BCI), also known as a Brain-Machine Interface (BMI), is a technology that enables direct communication between the brain and an external device, such as a computer or a machine, without the need for any muscular or peripheral nerve activity. Essentially, BCIs establish a direct pathway between the brain and an external device, allowing for bidirectional communication.
BCIs typically work by detecting and interpreting brain signals, which are then translated into commands that control external devices or provide feedback to the user. These brain signals can be detected through various methods, including electroencephalography (EEG), which measures electrical activity in the brain through electrodes placed on the scalp, or invasive techniques such as implanted electrodes.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
2S-ODIS: Two-Stage Omni-Directional Image Synthesis by Geometric Distortion Correction
SepPrune: Structured Pruning for Efficient Deep Speech Separation
Learning Local Implicit Fourier Representation for Image Warping
Personalizing Federated Medical Image Segmentation via Local Calibration
Improving EEG Signal Classification Accuracy Using Wasserstein Generative Adversarial Networks
Feature interpretability in BCIs: exploring the role of network lateralization
Improving SSVEP BCI Spellers With Data Augmentation and Language Models
Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfaces
Pseudocylindrical Convolutions for Learned Omnidirectional Image Compression
Deep Jansen-Rit Parameter Inference for Model-Driven Analysis of Brain Activity
A Temporal-Spectral Fusion Transformer with Subject-Specific Adapter for Enhancing RSVP-BCI Decoding
Guess What I Think: Streamlined EEG-to-Image Generation with Latent Diffusion Models
EEG motor imagery decoding: A framework for comparative analysis with channel attention mechanisms
Calibration-free online test-time adaptation for electroencephalography motor imagery decoding
Functional connectivity ensemble method to enhance BCI performance (FUCONE)
The more, the better? Evaluating the role of EEG preprocessing for deep learning applications
Auto-Compressing Subset Pruning for Semantic Image Segmentation
Time-space-frequency feature Fusion for 3-channel motor imagery classification
Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy
Towards Decoding Brain Activity During Passive Listening of Speech
Scalable Classifier-Agnostic Channel Selection for Multivariate Time Series Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.