diff --git a/src/assets/img/projects/yolov5_test.png b/src/assets/img/projects/yolov5_test.png
new file mode 100644
index 0000000..2836f5c
Binary files /dev/null and b/src/assets/img/projects/yolov5_test.png differ
diff --git a/src/assets/localization/en/localization.json b/src/assets/localization/en/localization.json
index 67d046a..c3669bf 100644
--- a/src/assets/localization/en/localization.json
+++ b/src/assets/localization/en/localization.json
@@ -120,7 +120,7 @@
         },
         "semantic": {
           "title": "Semantic Segmentation models study",
-          "text": "I installed three models on my laptop, Unet, Segnet and DeeplabV3, and trained them using the \"oxford_iiit_pet\" dataset ( from which the pictures on this page come from ). I searched about them and obtained various statistics and results, that I analysed and used to determine which one was the best Semantic Segmentation model back then.",
+          "text": "I installed three models on my laptop, Unet, Segnet and DeeplabV3, and trained them using the \"oxford_iiit_pet\" dataset ( from which the cat picture on this page comes from ). I searched about them and obtained various statistics and results, that I analysed and used to determine which one was the best Semantic Segmentation model back then.",
           "table": {
             "model": "Model",
             "accuracy": "Accuracy",
@@ -132,7 +132,7 @@
         },
         "human_recognition": {
           "title": "Human detection",
-          "text": "Along with the Semantic Segmentation, I was asked to find a way to recognize an human from a webcam stream. I chose the model YoloV5 to implement this functionality, and got some nice results."
+          "text": "Alongside with the Semantic Segmentation, I was asked to find a way to recognize an human from a webcam stream. I chose the model YoloV5 to implement this functionality, and got some nice results."
         }
       }
     }
diff --git a/src/views/projects/semanticSegmentationView.vue b/src/views/projects/semanticSegmentationView.vue
index 8d5a0b0..525aa58 100644
--- a/src/views/projects/semanticSegmentationView.vue
+++ b/src/views/projects/semanticSegmentationView.vue
@@ -54,6 +54,7 @@
 
       <h2>{{ $t("projects.semantic_segmentation.content.human_recognition.title") }}</h2>
       <p>{{ $t("projects.semantic_segmentation.content.human_recognition.text") }}</p>
+      <img :src="yolov5TestImg" id="yolo_img"/>
     </article>
   </template>
 
@@ -63,6 +64,7 @@
 
     import semanticSegmentationCover from "@/assets/img/semantic_segmentation.png";
     import hachinoheKosenImg from "@/assets/img/projects/hachinohe_kosen.png";
+    import yolov5TestImg from "@/assets/img/projects/yolov5_test.png";
 </script>
 
 <style scoped>
@@ -113,5 +115,10 @@
   table{
     margin: auto;
   }
+
+  #yolo_img{
+    width: 80%;
+    max-width: 600px;
+  }
 </style>
   
\ No newline at end of file