Summary of related works. by Yiming Kuang (22120458)

“…To demonstrate its strength, we benchmarked PiCCL against various state-of-the-art self-supervised algorithms on multiple datasets including CIFAR-10, CIFAR-100, and STL-10. …”

Results on STL-10 at 500 epoch. by Yiming Kuang (22120458)

“…To demonstrate its strength, we benchmarked PiCCL against various state-of-the-art self-supervised algorithms on multiple datasets including CIFAR-10, CIFAR-100, and STL-10. …”

Results on CIFAR-10 & CIFAR-100. by Yiming Kuang (22120458)

“…To demonstrate its strength, we benchmarked PiCCL against various state-of-the-art self-supervised algorithms on multiple datasets including CIFAR-10, CIFAR-100, and STL-10. …”

Speed and Memory Metrics. by Yiming Kuang (22120458)

“…To demonstrate its strength, we benchmarked PiCCL against various state-of-the-art self-supervised algorithms on multiple datasets including CIFAR-10, CIFAR-100, and STL-10. …”

Image augmentation methods. by Yiming Kuang (22120458)

“…To demonstrate its strength, we benchmarked PiCCL against various state-of-the-art self-supervised algorithms on multiple datasets including CIFAR-10, CIFAR-100, and STL-10. …”

Results on STL-10 with batch size = 256. by Yiming Kuang (22120458)

“…To demonstrate its strength, we benchmarked PiCCL against various state-of-the-art self-supervised algorithms on multiple datasets including CIFAR-10, CIFAR-100, and STL-10. …”

NFTool’s training state. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Empirical investigation of the heat exchanger. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Evaluate regression of values. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Eigen analysis of the correlation matrix. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Eigenvectors. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Iteration versus fitness function. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Matrix summary of investigated responses. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Nftool evaluate error histogram. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Visually represents the Pareto front solutions. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Flow chart. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Nftool error histogram. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Experimental and predicted regression of values. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Optimal parameters input parameters by nftool-GA. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”

Nftool best training performance. by B. Venkatesh (17202747)

“…By using genetic algorithms, Pareto front solutions that meet the requirements of decision-makers can be found. …”