The COVID19 pandemic, a unique and devastating respiratory disease outbreak, has affected global populations as the disease spreads rapidly. Recent Deep Learning breakthroughs may improve COVID19 prediction and forecasting as a tool of precise and fast detection, however, current methods are still being examined to achieve higher accuracy and precision. This study analyzed the collection contained 8055 CT image samples, 5427 of which were COVID cases and 2628 non COVID. The 9544 Xray samples included 4044 COVID patients and 5500 non COVID cases. The most accurate models are MobileNet V3 (97.872 percent), DenseNet201 (97.567 percent), and GoogleNet Inception V1 (97.643 percent). High accuracy indicates that these models can make many accurate predictions, as well as others, are also high for MobileNetV3 and DenseNet201. An extensive evaluation using accuracy, precision, and recall allows a comprehensive comparison to improve predictive models by combining loss optimization with scalable batch normalization in this study. Our analysis shows that these tactics improve model performance and resilience for advancing COVID19 prediction and detection and shows how Deep Learning can improve disease handling. The methods we suggest would strengthen healthcare systems, policymakers, and researchers to make educated decisions to reduce COVID19 and other contagious diseases. CCS CONCEPTS Covid,Deep Learning, Image Processing KEYWORDS Covid, Deep Learning, DenseNet201, MobileNet, ResNet, DenseNet, GoogleNet, Image Processing, Disease Detection.

翻译：COVID19大流行作为一种独特且破坏性的呼吸道疾病爆发，随着疾病快速传播，已对全球人口造成影响。近期深度学习的突破可能为COVID19的预测与预报提供精准快速检测的工具，然而现有方法仍需进一步检验以实现更高的准确度与精确度。本研究分析了包含8055张CT图像样本的数据集，其中5427例为COVID病例，2628例为非COVID病例。9544张X射线样本则包括4044例COVID患者和5500例非COVID病例。最准确的模型为MobileNet V3（准确率97.872%）、DenseNet201（97.567%）和GoogleNet Inception V1（97.643%）。高准确率表明这些模型能做出大量准确预测，同时MobileNetV3和DenseNet201的其他指标也表现出高水准。通过使用准确率、精确度和召回率进行广泛评估，本研究结合损失优化与可扩展批归一化，为改进预测模型提供了全面比较。我们的分析表明，这些策略能提升模型在改进COVID19预测与检测方面的性能与鲁棒性，并展示了深度学习如何增强疾病应对能力。我们提出的方法将助力医疗系统、政策制定者和研究人员做出明智决策，以减轻COVID19及其他传染性疾病的影响。CCS概念：COVID、深度学习、图像处理。关键词：COVID、深度学习、DenseNet201、MobileNet、ResNet、DenseNet、GoogleNet、图像处理、疾病检测。