Applications with adaptability are widely available on the edge devices with energy
harvesting capabilities. For their runtime quality optimization, however, current approaches …

On the one hand, accelerating convolution neural networks (CNNs) on FPGAs requires ever
increasing high energy efficiency in the edge computing paradigm. On the other hand …

The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical
trials and healthcare procedures. Thanks to innovative technologies, latest-generation …

The rising demand for renewable energy supply in standalone computing devices has led to
the emergence of vibration energy harvesting (VEH) to overcome technical and …

Stereo matching is a promising approach for smart vehicles to find the depth of nearby
objects. Transforming a traditional stereo matching algorithm to its adaptive version has …

While FPGA has been recognized as a promising platform to accelerate Convolutional
Neural Networks (CNNs) in embedded computing given its high flexibility and power …

Dynamic Voltage and Frequency Scaling (DVFS) has been extensively applied as a system-
level methodology for energy optimization or temperature control. But current DVFS systems …

Feature detection is essential to a large number of vision-based applications. Among the
approaches available, keypoint detection-based ones, eg, SIFT, SURF, and ORB, are very …

Abstract The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple
clinical trials and healthcare procedures. It relies on novel, very accurate and compact …

The present disclosure provides an adaptive stereo matching optimization method,
apparatus, and device, and a storage medium. The method includes: acquiring images of at …