AIMC Topic: Vision, Ocular

Clear Filters Showing 31 to 40 of 138 articles

Understanding Human Object Vision: A Picture Is Worth a Thousand Representations.

Annual review of psychology
Objects are the core meaningful elements in our visual environment. Classic theories of object vision focus upon object recognition and are elegant and simple. Some of their proposals still stand, yet the simplicity is gone. Recent evolutions in beha...

On the role of feedback in image recognition under noise and adversarial attacks: A predictive coding perspective.

Neural networks : the official journal of the International Neural Network Society
Brain-inspired machine learning is gaining increasing consideration, particularly in computer vision. Several studies investigated the inclusion of top-down feedback connections in convolutional networks; however, it remains unclear how and when thes...

On the Sufficient Condition for Solving the Gap-Filling Problem Using Deep Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems
Deep convolutional neural networks (DCNNs) are routinely used for image segmentation of biomedical data sets to obtain quantitative measurements of cellular structures like tissues. These cellular structures often contain gaps in their boundaries, le...

Sensor Data Fusion Based on Deep Learning for Computer Vision Applications and Medical Applications.

Sensors (Basel, Switzerland)
Sensor fusion is the process of merging data from many sources, such as radar, lidar and camera sensors, to provide less uncertain information compared to the information collected from single source [...].

The Navigation System of a Logistics Inspection Robot Based on Multi-Sensor Fusion in a Complex Storage Environment.

Sensors (Basel, Switzerland)
To reliably realize the functions of autonomous navigation and cruise of logistics robots in a complex logistics storage environment, this paper proposes a new robot navigation system based on vision and multiline lidar information fusion, which can ...

A Novel Velocity-Based Control in a Sensor Space for Parallel Manipulators.

Sensors (Basel, Switzerland)
It is a challenging task to track objects moving along an unknown trajectory. Conventional model-based controllers require detailed knowledge of a robot's kinematics and the target's trajectory. Tracking precision heavily relies on kinematics to infe...

Object-Based Change Detection Algorithm with a Spatial AI Stereo Camera.

Sensors (Basel, Switzerland)
This paper presents a real-time object-based 3D change detection method that is built around the concept of semantic object maps. The algorithm is able to maintain an object-oriented metric-semantic map of the environment and can detect object-level ...

Massive-Scale Aerial Photo Categorization by Cross-Resolution Visual Perception Enhancement.

IEEE transactions on neural networks and learning systems
Categorizing aerial photographs with varied weather/lighting conditions and sophisticated geomorphic factors is a key module in autonomous navigation, environmental evaluation, and so on. Previous image recognizers cannot fulfill this task due to thr...

Sensor-level computer vision with pixel processor arrays for agile robots.

Science robotics
Vision processing for control of agile autonomous robots requires low-latency computation, within a limited power and space budget. This is challenging for conventional computing hardware. Parallel processor arrays (PPAs) are a new class of vision se...

Moving Object Detection Based on Fusion of Depth Information and RGB Features.

Sensors (Basel, Switzerland)
The detection of moving objects is one of the key problems in the field of computer vision. It is very important to detect moving objects accurately and rapidly for automatic driving. In this paper, we propose an improved moving object detection meth...