Shmuel Peleg

What is he best known for?

The fields of study he is best known for:

• Artificial intelligence
• Computer vision
• Geometry

Shmuel Peleg mainly investigates Artificial intelligence, Computer vision, Image processing, Computer graphics and Image resolution. His Artificial intelligence study combines topics in areas such as Motion and Time delay and integration. Many of his studies on Computer vision involve topics that are commonly interrelated, such as Resolution.

The Image processing study combines topics in areas such as Graph, Image segmentation and Image formation. His research in Computer graphics intersects with topics in Object, Panorama, Field of view and Reference frame. His studies in Image resolution integrate themes in fields like Pixel, Subpixel rendering, Superresolution and Image texture.

His most cited work include:

• Improving resolution by image registration (1602 citations)
• Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency (758 citations)
• Multiple Resolution Texture Analysis and Classification (693 citations)

What are the main themes of his work throughout his whole career to date?

Shmuel Peleg spends much of his time researching Artificial intelligence, Computer vision, Computer graphics, Image processing and Image. His multidisciplinary approach integrates Artificial intelligence and Process in his work. His work on Image resolution, Motion estimation, Motion field and Optical flow as part of his general Computer vision study is frequently connected to Geography, thereby bridging the divide between different branches of science.

His Image resolution study also includes

• Resolution together with Sub-pixel resolution,
• Image restoration together with Feature detection. His work deals with themes such as Structure from motion and Match moving, which intersect with Motion field. His Computer graphics study integrates concerns from other disciplines, such as Panorama, Parallax and Video camera.

He most often published in these fields:

• Artificial intelligence (75.88%)
• Computer vision (64.91%)
• Computer graphics (20.61%)

What were the highlights of his more recent work (between 2011-2021)?

• Artificial intelligence (75.88%)
• Computer vision (64.91%)
• Speech recognition (7.46%)

In recent papers he was focusing on the following fields of study:

Shmuel Peleg focuses on Artificial intelligence, Computer vision, Speech recognition, Artificial neural network and Epipolar geometry. His study in Pattern recognition extends to Artificial intelligence with its themes. Computer vision connects with themes related to Similarity measure in his study.

His work is dedicated to discovering how Speech recognition, Noise are connected with Filter and other disciplines. His biological study spans a wide range of topics, including Subtraction, Roman numerals, Arithmetic and Inference. He interconnects Algorithm and Silhouette in the investigation of issues within Epipolar geometry.

Between 2011 and 2021, his most popular works were:

• Temporal Segmentation of Egocentric Videos (138 citations)
• Compact CNN for indexing egocentric videos (77 citations)
• Visual Speech Enhancement. (65 citations)

In his most recent research, the most cited papers focused on:

• Artificial intelligence
• Computer vision
• Algorithm

His scientific interests lie mostly in Artificial intelligence, Computer vision, Speech recognition, Convolutional neural network and Video browsing. His work often combines Artificial intelligence and Optical imaging studies. His Computer vision study combines topics from a wide range of disciplines, such as Search engine indexing and Automatic summarization.

Shmuel Peleg combines subjects such as Artificial neural network and Noise with his study of Speech recognition. His Convolutional neural network study incorporates themes from Intelligibility, Speech reconstruction and Speechreading. His work carried out in the field of Video browsing brings together such families of science as Computer graphics and Feature.