diff --git a/art/attacks/evasion/fast_gradient.py b/art/attacks/evasion/fast_gradient.py
index 80571469b7..0867332756 100644
--- a/art/attacks/evasion/fast_gradient.py
+++ b/art/attacks/evasion/fast_gradient.py
@@ -476,7 +476,7 @@ def _apply_perturbation(
     ) -> np.ndarray:
 
         perturbation_step = eps_step * perturbation
-        if perturbation_step.dtype != object:
+        if perturbation_step.dtype is not object:
             perturbation_step[np.isnan(perturbation_step)] = 0
         else:
             for i, _ in enumerate(perturbation_step):
@@ -489,7 +489,7 @@ def _apply_perturbation(
         x = x + perturbation_step
         if self.estimator.clip_values is not None:
             clip_min, clip_max = self.estimator.clip_values
-            if x.dtype == object:
+            if x.dtype is object:
                 for i_obj in range(x.shape[0]):
                     x[i_obj] = np.clip(x[i_obj], clip_min, clip_max)
             else:
diff --git a/art/estimators/tensorflow.py b/art/estimators/tensorflow.py
index d175d23fd8..f0d54085fb 100644
--- a/art/estimators/tensorflow.py
+++ b/art/estimators/tensorflow.py
@@ -181,7 +181,7 @@ def _apply_preprocessing(self, x, y, fit: bool = False) -> tuple[Any, Any]:
 
         input_is_tensor = isinstance(x, tf.Tensor)
 
-        if self.all_framework_preprocessing and not (not input_is_tensor and x.dtype == object):
+        if self.all_framework_preprocessing and not (not input_is_tensor and x.dtype is object):
             # Convert np arrays to torch tensors.
             if not input_is_tensor:
                 x = tf.convert_to_tensor(x)