[HTML][HTML] Deep-learning-based approaches for semantic segmentation of natural scene images: A review
The task of semantic segmentation holds a fundamental position in the field of computer
vision. Assigning a semantic label to each pixel in an image is a challenging task. In recent …
vision. Assigning a semantic label to each pixel in an image is a challenging task. In recent …
A survey of data partitioning and sampling methods to support big data analysis
Computer clusters with the shared-nothing architecture are the major computing platforms
for big data processing and analysis. In cluster computing, data partitioning and sampling …
for big data processing and analysis. In cluster computing, data partitioning and sampling …
The next generation of deep learning hardware: Analog computing
Initially developed for gaming and 3-D rendering, graphics processing units (GPUs) were
recognized to be a good fit to accelerate deep learning training. Its simple mathematical …
recognized to be a good fit to accelerate deep learning training. Its simple mathematical …
Efficient AI system design with cross-layer approximate computing
Advances in deep neural networks (DNNs) and the availability of massive real-world data
have enabled superhuman levels of accuracy on many AI tasks and ushered the explosive …
have enabled superhuman levels of accuracy on many AI tasks and ushered the explosive …
A two-stage operand trimming approximate logarithmic multiplier
We present an approximate logarithmic multiplier with two-stage operand trimming, which
prioritises area and energy consumption while retains acceptable accuracy. The multiplier …
prioritises area and energy consumption while retains acceptable accuracy. The multiplier …
Exploiting approximate computing for deep learning acceleration
CY Chen, J Choi, K Gopalakrishnan… - … , Automation & Test …, 2018 - ieeexplore.ieee.org
Deep Neural Networks (DNNs) have emerged as a powerful and versatile set of techniques
to address challenging artificial intelligence (AI) problems. Applications in domains such as …
to address challenging artificial intelligence (AI) problems. Applications in domains such as …
On the design of logarithmic multiplier using radix-4 booth encoding
R Pilipović, P Bulić - IEEE access, 2020 - ieeexplore.ieee.org
This paper proposes an energy-efficient approximate multiplier which combines radix-4
Booth encoding and logarithmic product approximation. Additionally, a datapath pruning …
Booth encoding and logarithmic product approximation. Additionally, a datapath pruning …
A cross-layer gate-level-to-application co-simulation for design space exploration of approximate circuits in HEVC video encoders
A cross-layer design space exploration (DSE) method based on a proposed co-simulation
technique is presented herein. The proposed method is demonstrated evaluating the …
technique is presented herein. The proposed method is demonstrated evaluating the …
Security: The dark side of approximate computing?
Approximate computing promises significant advantages over more traditional computing
architectures with respect to circuit area, performance, power efficiency, flexibility, and cost …
architectures with respect to circuit area, performance, power efficiency, flexibility, and cost …
[HTML][HTML] A hybrid radix-4 and approximate logarithmic multiplier for energy efficient image processing
Multiplication is an essential image processing operation commonly implemented in
hardware DSP cores. To improve DSP cores' area, speed, or energy efficiency, we can …
hardware DSP cores. To improve DSP cores' area, speed, or energy efficiency, we can …