목록2024/10 (15)
UOMOP
PSNR vs FLOPs
% 기존 데이터 입력 (FLOPs 데이터)snr_512 = [30, 20, 10, 0];flops_proposed_512 = [20855.182, 20073.754, 18959.42, 17114.83];flops_TopK_512 = [37627.156, 32831.124, 25740.668, 21987.248];flops_Random_512 = [42444.78, 36116.336, 25495.256, 19640.542];snr_256 = [30, 20, 10, 0];flops_proposed_256 = [26347.008, 23197.228, 19014.698, 17960.544];flops_TopK_256 = [36023.62, 31121.048, 23387.992, 21973.838];flops_R..
SNR vs PSNR graph
% 기존 데이터 입력snr_512 = [30, 20, 10, 0];psnr_proposed_512 = [30.99, 28.68, 24.98, 21.05];psnr_TopK_512 = [29.99, 27.82, 24.19, 20.41];psnr_Random_512 = [30.00, 27.38, 23.24, 19.02];snr_256 = [30, 20, 10, 0];psnr_proposed_256 = [27.35, 25.98, 23.23, 20.20];psnr_TopK_256 = [26.80, 25.34, 22.61, 19.32];psnr_Random_256 = [26.92, 25.24, 21.69, 17.96];% DeepJSCC 데이터 추가psnr_DeepJSCC_256 = [19.638, 23.318,..
CBS (alpha: 2.1, beta: 0.6)dim:512, snr:30, alpha:2.1, beta:0.6 Lv1:2321, Lv2:321, Lv3:230, Lv4:7128 final FLOPs : 20855.182 Average PSNR over 10000 images: 29.99 Data loaded from files. dim:512, snr:20, alpha:2.1, beta:0.6 Lv1:1627, Lv2:995, Lv3:680, Lv4:6698 final FLOPs : 20073.754 Average PSNR over 10000 images: 27.68 Data loaded from files. dim:512, snr:10, alpha:2.1, beta:0.6 Lv1:476, Lv2:7..
% alpha와 beta의 값들alpha_values = [0.1, 0.4, 0.7, 1.0, 1.3, 1.6];beta_values = [0.1, 0.4, 0.7, 1.0, 1.3, 1.6];% 데이터: alpha, beta, dim, snr, Average PSNR, FLOPsdata = [ 0.1, 0.1, 512, 30, 30.17, 42615.213; 0.1, 0.4, 512, 30, 30.13, 41735.868; 0.1, 0.7, 512, 30, 30.04, 40109.326; 0.1, 1.0, 512, 30, 29.89, 37927.21; 0.1, 1.3, 512, 30, 29.69, 35437.803; 0.1, 1.6, 512, 30, 29.46, 3313..
% 데이터: alpha, beta, dim, snr, Average PSNR, FLOPsdata = [ 0.1, 0.1, 512, 30, 30.06, 45269.61; 0.1, 0.4, 512, 30, 30.05, 45131.627; 0.1, 0.7, 512, 30, 30.03, 44734.679; 0.1, 1.0, 512, 30, 29.98, 43972.61; 0.1, 1.3, 512, 30, 29.87, 42476.44; 0.1, 1.6, 512, 30, 29.68, 40356.324; 0.4, 0.1, 512, 30, 30.06, 45269.61; 0.4, 0.4, 512, 30, 30.05, 45129.967; 0.4, 0.7, 512, 30, 30..
CBS alpha, beta
% alpha와 beta의 값들alpha_values = [0.1, 0.4, 0.7, 1.0, 1.3, 1.6];beta_values = [0.1, 0.4, 0.7, 1.0, 1.3, 1.6];% 데이터: alpha, beta, dim, snr, Average PSNR, FLOPsdata = [ 0.1, 0.1, 512, 30, 30.53, 39008.573; 0.1, 0.4, 512, 30, 30.46, 37107.607; 0.1, 0.7, 512, 30, 30.29, 33694.062; 0.1, 1.0, 512, 30, 30.06, 30121.08; 0.1, 1.3, 512, 30, 29.79, 27204.84; 0.1, 1.6, 512, 30, 29.54, 25425..