Google DeepMind released AlphaGenome on January 28, an AI model that predicts how DNA sequences translate into biological functions, processing up to one million base-pairs at once and outperforming ...

Abstract: We consider a windowed decoding scheme for LDPC convolutional codes that is based on the belief-propagation (BP) algorithm. We discuss the advantages of this decoding scheme and identify ...

Abstract: Due to the growing interest in applying tail-biting convolutional coding techniques in real-time communication systems, fast decoding of tail-biting convolutional codes has become an ...

We released DDN, the follow-up work of NBED. Main features: By introducing Evidence Lower Bound loss and learnable Gaussian distributions, DDN is capable of generating multi-granularity edges. The ODS ...

RGB-depth (RGB-D) salient object detection (SOD) recently has attracted increasing research interest, and many deep learning methods based on encoder-decoder architectures have emerged. However, most ...

Thanks to the author for your contribution! I'm using the convolutional code of libcorrect. I have tested the libcorrect with rate from 2 to 10 with order 8 and I found that when the rate is 2 to 8 ...

However, some releases propose LDPC codes for error-corrections due to the relative complexity of turbo codes decoder implementations as well as the success of LDPC codes in achieving the same ...

Summary: Combining artificial intelligence technology with raw data from brain activity, researchers accelerate the understanding of how neural activity impacts specific behaviors. An artificial ...

Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings. Even so, interpretation of this data requires ...