Model selection based on best fit. by Angelina Mageni Lutambi (22097223)

“…<div><p>Malaria remains a significant public health challenge, particularly among vulnerable populations in high-burden countries like Tanzania. …”

Specifications of prototypes of RSSCA system. by Ngoc-Hai Vu (22290844)

“…Compared to conventional PV systems, the RSSCA offers improved light uniformity, better land-use efficiency, and significantly higher electricity generation. …”

Design of a RSSCA system for agriculture. by Ngoc-Hai Vu (22290844)

“…Compared to conventional PV systems, the RSSCA offers improved light uniformity, better land-use efficiency, and significantly higher electricity generation. …”

Illinois agility test [22]. by Rıdvan Ergin (22265431)

“…</p><p>Results</p><p>A positive significant relationship was found between age and years of sports (r = .759; p < 0.01) and vertical jump (r = .657; p < 0.01) in male handball players, as well as a positive significant relationship between body weight and agility (r = .621; p < 0.05). …”

Conceptual model created for research. by Rıdvan Ergin (22265431)

“…</p><p>Results</p><p>A positive significant relationship was found between age and years of sports (r = .759; p < 0.01) and vertical jump (r = .657; p < 0.01) in male handball players, as well as a positive significant relationship between body weight and agility (r = .621; p < 0.05). …”

Pre- & post awareness session scores. by Stavia Turyahabwe (9925935)

“…TB treatment adherence rates among TB patients using VOT was significantly better (<i>p</i><0.01) than those using DOTS.…”

VOT vs DOTS TB treatment adherence rates. by Stavia Turyahabwe (9925935)

“…TB treatment adherence rates among TB patients using VOT was significantly better (<i>p</i><0.01) than those using DOTS.…”

Sample size and duration of the pilot study. by Stavia Turyahabwe (9925935)

“…TB treatment adherence rates among TB patients using VOT was significantly better (<i>p</i><0.01) than those using DOTS.…”

MGPC module. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Comparative experiment. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Pruning experiment. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Parameter setting table. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

DTADH module. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Ablation experiment. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Multi scale detection. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

MFDPN module. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Detection effect of different sizes. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Radar chart comparing indicators. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

MFD-YOLO structure. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”

Detection results of each category. by Bo Tong (2138632)

“…Experimental results indicate that at a pruning level of 1.5, mAP@0.5 and mAP@0.5:0.95 improved by 3.9% and 4.6%, respectively, while computational load decreased by 21% and parameter count dropped by 53%. …”