Abstract: This article presents a new deep-learning architecture based on an encoder-decoder framework that retains contrast while performing background subtraction (BS) on thermal videos. The ...
“By using unexpected and unusual codes and symbols and making the visible web address look less suspicious and more like a normal website, the encoding technique is designed to trick security systems ...
Create a URL encoder/decoder tool to the encoder/decoder Tool Group, following the Base64 Text encoder/decoder tool that already exists. It should follow consistent code structure from Base64 Text ...
Beyond tumor-shed markers: AI driven tumor-educated polymorphonuclear granulocytes monitoring for multi-cancer early detection. Clinical outcomes of a prospective multicenter study evaluating a ...
This base64 encoder/decoder is faster than the stdlib base64 package. Encoding is 70% faster on ARM64 (Mac book M2) and 36% on AMD64 (i5 11th Gen). Decoding MIME encoded base64, which is base64 with a ...
Abstract: Speech enhancement (SE) models based on deep neural networks (DNNs) have shown excellent denoising performance. However, mainstream SE models often have high structural complexity and large ...
Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...
CNNs are specialized deep neural networks for processing data with a grid-like topology, such as images. A CNN automatically detects the important features without any human supervision. They are ...
Base64 encoding is a common method to encode binary data into an ASCII string format, making it easier to transmit data over networks that only support text. This can include embedding image data in ...
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